SALoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs-Reference-Cited by-同舟云学术

SALoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
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Author:

Park Seongyeon¹,Kim Hajin¹,Ahmad Tanveer²,Ahmed Nauman²,Al-Ars Zaid²,Hofstee H. Peter²,Kim Youngsok²,Lee Jinho²

Affiliation:

1. Yonsei University

2. TU Delft

Funder

National Research Foundation of Korea (NRF)

Publisher

IEEE

Link

Reference62 articles.

4. Exploring modern GPU memory system design challenges through accurate modeling;khairy;ArXiv Preprint,2018

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